Urbanization plays a crucial role in facilitating the integration of population growth, industrial development, economic expansion, and energy consumption. In this paper, we aim to examine the relationships between CO2 emissions and various factors including economic growth, urbanization, financial development, and energy consumption within Pakistan’s building sector. The study utilizes annual data spanning from 1990 to 2020. To analyze the cointegration relationship between these variables, we employ the quantile autoregressive distributed lag error correction model (QARDL-ECM). The findings of this research provide evidence supporting the presence of an asymmetric and nonlinear long-term relationship between the variables under investigation. Based on these results, we suggest the implementation of tariffs on nonrenewable energy sources and the formulation of policies that promote sustainable energy practices. By doing so, policymakers and architects can effectively contribute to minimising environmental damage. Overall, this study offers valuable insights that can assist policymakers and architects in making informed decisions to mitigate environmental harm while fostering sustainable development.

COVID-19 has presented considerable challenges to fiscal budget allocations in developing countries, significantly affecting decisions regarding number of investments in the transport sector where precise resource allocation is required. Elucidating the long-term relationship between public transport investment and economic growth might enable policymaker to effectively make a decision in regard to those budget allocation. Our paper then utilizes Thailand as a case study to analyze the effects on economic growth in a developing country context. The study employs Cointegration and Vector Error Correction Model (VECM) techniques to account for long-term correlations among explanatory variables during 1991–2019. The statistical findings reveal a significantly positive correlation between transport investment and economic growth by indicating an increase of 0.937 in economic growth for every one-percent increment in transport investment (S.D. = 0.024, p < 0.05). This emphasizes the potential of expanding the transport investment to recover Thailand’s economy. Furthermore, in terms of short-term adjustments, our results indicate that transport investment can significantly mitigate the negative impact of external shocks by 0.98 percent (p < 0.05). These findings assist policymakers in better managing national budget allocations in the post-Covid-19 period, allowing them to estimate the duration of crowding-out effects induced by shocks more effectively.

 In the face of growing disruptions within the unconventional business environment, this study focuses on enhancing supply chain resilience through strategically reforming resources. It highlights the importance of understanding the dynamics and interactions of resources to tackle supply chain vulnerability (SCV) in the manufacturing sector. Employing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology alongside an adapted Analytic Network Process (ANP), the research investigates supply chain vulnerabilities in Pakistan’s large-scale manufacturing (LSM) public sector firms. The DANP method, through expert questionnaires, helps validate a theoretical framework by assessing the interconnectedness of supply chain readiness dimensions and criteria. Findings underscore Resource Reformation (RR) as a critical dimension, with the positive restructuring of resources identified as pivotal for public sector firms to align their operations with disruption magnitudes, advocating for a detailed analysis of resource utilization.

The complex interactions of industrial Policy, structural transformation, economic growth, and competitive strategy within regional industries are examined in this research. Using a dynamic capabilities framework, the study examines the mediating roles of organizational innovation and adaptability in the link between competitiveness and macroeconomic variables. A two-way fixed effects model is used in this study to examine the influence of structural transformation (ST) on Industrial Policy (IP). Using regional data covering the years 2010 to 2022, the research undertaken in this paper explores the dynamics of the Indonesian economy by empirically assessing the consequences of structural change on industrial Policy. In order to establish a comprehensive model that clarifies the mechanisms through which industrial policies and structural shifts impact the development of dynamic capabilities, ultimately influencing competitiveness strategies, this research draws on a large amount of empirical data and integrates insights from seminal works. Our research adds to our knowledge of strategic management in regional industries by providing detailed information on how economic development and policy interventions influence businesses’ ability to adapt and gain a competitive edge. In addition to advancing scholarly discourse, this study offers business executives and politicians valuable insights for managing the intricacies of global economic processes.

China’s economic structure has made subtle changes with the development of digital economy. Along with the marginal diminishing effect of Chinese monetary policies and the increase of the overall leverage ratio, the Chinese economic growth mode of relying on real estate, trade and infrastructure construction in the past will not be sustainable in the next decade. This paper makes a theoretical analysis on the reduction of the search cost in digital economy. Also, this paper used empirical methods to study the relationship between China’s economic growth and digital infrastructure construction. In conclusion, the digital economy has reduced the search cost for people, and big data will become a product factor participating in labor distribution. In addition, this paper proposes for the first time that digital economy can effectively restrain inflation. The Chinese government needs to attach importance to the issue that current internet enterprise oligarchs will probably monopolize the usage of big data in the development of digital economy in the future and become the obstacle to effective economic growth. In addition, close attention should be paid to the vulnerabilities of financial and taxation systems for digital economic entities to avoid continuous disguised tax subsidies to internet oligarchs, thus preventing industrial monopoly.

The significance of remittances to the Vietnamese economy necessitates investigating how they affect the value of the Vietnamese currency and other macroeconomic factors. Macroeconomic articles struggle to discover their impact on economic development, but measured remittances by migrant workers have recently soared. There is no academic study that has examined this phenomenon in Vietnam. This study uses wavelet frameworks to analyze the lead-lag nexus between exchange rates, remittances, and economic growth in Vietnam in time-frequency domains from 1995 to 2020. Overall, we find that: (i) remittances enhance economic growth in the short and medium run; (ii) exchange rates boost remittances in the short and medium run; (iii) exchange rates promote GDP in all frequency and time domains. Moreover, the partial wavelet coherence and multiple wavelet coherence frameworks also offered evidence supporting the wavelet coherence approach. More importantly, the outcomes of wavelet-based Granger causality unveil that there is two-way causality between the selected indicators, which means that all the indicators can predict each other at different frequencies. Our empirical results provide meaningful information for market participants and policymakers.